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深度学习将机械模型与单细胞转录组学数据联系起来,揭示了对DNA损伤的反应中的转录爆发

Zhiwei Huang^1,2, Songhao Luo³, Zihao Wang^1,2

¹Guangdong Province Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou, China.

|March 4, 2026

概括

DeepTX是一个新的深度学习框架,从单细胞RNA测序数据中推断出全基因组的转录爆发. 这揭示了基因表达动态或转录爆发如何影响DNA损伤后的细胞命运决定.

科学领域:

分子生物学分子生物学
基因组学就是基因组学.
计算生物学计算生物学

背景情况:

细胞利用静态基因表达程序来决定命运,例如分化或亡.
了解全基因组转录突破对DNA损伤的反应是一个挑战.

研究的目的:

开发一个可解释和可扩展的深度学习框架 (DeepTX) 来从单细胞RNA测序 (scRNA-seq) 数据中推断全基因组转录突发动力学.
将机械模型与scRNA-seq数据连接起来,以分析转录突破动态.

主要方法:

开发了DeepTX,这是一个集机械模型和scRNA-seq数据的深度学习框架.
将DeepTX应用于DNA损伤药物治疗中的scRNA-seq数据集.
推断了全基因组的转录突发动力学,并分析了它们与细胞命运的相关性.

主要成果:

从scRNA-seq数据中,DeepTX准确地推断出转录突发动力学.
不同的DNA损伤药物诱导了不同的转录突破模式.
5'--2'-脱氧氨治疗增加了爆发大小,与差异化相关.
5-甲治疗调节了爆发频率,与亡或生存相关.

结论:

DeepTX能够从单细胞转录组学中推断全基因组的转录爆发.
转录性爆发动态与DNA损伤后的细胞命运决定有关.
该框架可以产生关于爆发动态和细胞命运之间的关系的假设.

关键词:

对DNA损伤的反应反应细胞命运决定的决定计算生物学是计算生物学.深度学习是一种深度学习.人类人类人类人类人类人类人类这里是鼠标鼠标鼠标鼠标鼠标鼠标.一个单细胞RNA测序.停滞性基因表达停滞性基因表达系统生物学系统生物学转录性爆发是指转录性爆发.

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